Performance Modeling and Workflow Scheduling of Microservice-Based Applications in Clouds

• Published in: IEEE transactions on parallel and distributed systems Vol. 30; no. 9; pp. 2114 - 2129
• Main Authors: Bao, Liang, Wu, Chase, Bu, Xiaoxuan, Ren, Nana, Shen, Mengqing
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Benchmark testing; Cloud computing; Computational modeling; Computer architecture; Computer simulation; Microservice; Modelling; performance modeling and prediction; Performance prediction; Predictive models; Processor scheduling; Scheduling; Task scheduling; Workflow
• ISSN: 1045-9219; 1558-2183
• DOI: 10.1109/TPDS.2019.2901467

Microservice has been increasingly recognized as a promising architectural style for constructing large-scale cloud-based applications within and across organizational boundaries. This microservice-based architecture greatly increases application scalability, but meanwhile incurs an expensive performance overhead, which calls for a careful design of performance modeling and task scheduling. However, these problems have thus far remained largely unexplored. In this paper, we develop a performance modeling and prediction method for independent microservices, design a three-layer performance model for microservice-based applications, formulate a Microservice-based Application Workflow Scheduling problem for minimum end-to-end delay under a user-specified Budget Constraint (MAWS-BC), and propose a heuristic microservice scheduling algorithm. The performance modeling and prediction method are validated and justified by experimental results generated through a well-known microservice benchmark on disparate computing nodes, and the performance superiority of the proposed scheduling solution is illustrated by extensive simulation results in comparison with existing algorithms.